conftrace_
← Machine Learning
Machine Learning ›

Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

1
52
337
806
3400
3289
'00
'05
'10
'15
'20
'25

Papers (including subtopics)

Learning Multiple Tasks with a Sparse Matrix-Normal Penalty NIPS 2010
Network Flow Algorithms for Structured Sparsity NIPS 2010
Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets NIPS 2010
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs NIPS 2010
Learning Bounds for Importance Weighting NIPS 2010
A Reduction from Apprenticeship Learning to Classification NIPS 2010
Extensions of Generalized Binary Search to Group Identification and Exponential Costs NIPS 2010
Scrambled Objects for Least-Squares Regression NIPS 2010
Error Propagation for Approximate Policy and Value Iteration NIPS 2010
PAC-Bayesian Model Selection for Reinforcement Learning NIPS 2010
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm NIPS 2010
Worst-case bounds on the quality of max-product fixed-points NIPS 2010
A rational decision making framework for inhibitory control NIPS 2010
Policy gradients in linearly-solvable MDPs NIPS 2010
Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework NIPS 2010
Learning concept graphs from text with stick-breaking priors NIPS 2010
Fast Large-scale Mixture Modeling with Component-specific Data Partitions NIPS 2010
Improvements to the Sequence Memoizer NIPS 2010
Efficient Minimization of Decomposable Submodular Functions NIPS 2010
Implicit Differentiation by Perturbation NIPS 2010
The Maximal Causes of Natural Scenes are Edge Filters NIPS 2010
Regularized estimation of image statistics by Score Matching NIPS 2010
Exact inference and learning for cumulative distribution functions on loopy graphs NIPS 2010
Spectral Regularization for Support Estimation NIPS 2010
Smoothness, Low Noise and Fast Rates NIPS 2010